Indoor Location System Based On WiFi And Multi-user Group

With the development of technology,location-based services(LBS)gradually enter people's daily lives.GPS / Beidou and other satellite positioning system cannot be used for positioning in the indoor environment,so it is difficult to quickly determine people's own location.Therefore,the indoor positioning technology has become a hot research.At present,WIFI(Wireless Fidelity)technology gradually developed.WIFI access points have been deployed in many buildings,and it provides favorable conditions for the application and popularization of WIFI-based indoor positioning technology.At present,there are WIFI indoor positioning methods based on WIFI fingerprint database and wireless channel model,but their positioning accuracy is not high enough.In order to improve the positioning accuracy,the researchers proposed a variety of multi-user coordination indoor positioning method based on error diversity,triangular computing and so on.The increased accuracy of collaborative positioning method based on error diversity is limited,and the complexity of the method based on triangulation is higher.This paper focuses on the indoor localization method based on WIFI fingerprint database.On this basis,this paper proposes a multi-user cooperative positioning algorithm based on coustic ranging and multipoint topological approximation.The entire indoor positioning system is realized on the Android and Windows / Linux platform.In this paper,the method of indoor localization based on WIFI fingerprint database is studied deeply.The simulation of the whole positioning system is verified by Matlab,and the key parameters of the positioning system are determined and field test is carried out.Based on the field test results,an indoor positioning algorithm based on fingerprint database secondary correction is proposed.This algorithm improves the positioning accuracy to a certain extent by removing the reference points in the database which have little reference value and the unsuitable nearest neighbor in the precise positioning stage.Secondly,this paper introduces the existing multi-user collaborative indoor positioning algorithms,and then studies the multi-user group co-location algorithm based on WIFI and acoustic ranging.In this paper,we propose a ranging method based on multi-frequency audible acoustic amplitude summation.After the distance measurement is completed,the multi-point topological approximation co-localization algorithm proposed in this paper is used to deal with the WIFI positioning results and the sound wave ranging results,which greatly improves the positioning accuracy.Then,in order to further improve the positioning accuracy,this paper uses the Kalman filter to track the trajectory of the mobile terminal equipment.In order to solve the problem that the tracking error is large when the mobile terminal equipment is turned around using the standard Kalman filter,this paper proposes a Kalman filter algorithm combined with the indoor map.This algorithm uses the information of the indoor map and the speed direction estimation of the mobile terminal equipment to judge the turn,and adjusts the parameters of the Kalman filter in the case of turning,which greatly improves the tracking accuracy at the corner.Finally,the client of the indoor positioning system is realized on the Android platform.The positioning management service system is achieved on the Windows / Linux platform.The author has conducted field tests in some areas on the second floor of the school main building,and verifies the performance of the proposed positioning and tracking algorithm.The indoor positioning system in this paper improves the positioning accuracy of traditional WIFI positioning technology,and provides a basic guarantee for location-based services.